Rarely media files may have one or multiple
empty streams when they are badly formatted.
The extract metadata code would crash when that happened.
We now avoid crashing and create a clean file
from the bad one to make sure API calls with that data
works properly (observed some failures otherwise
in my tests).
* Removed constraint on file extension
* Infer audio/video streams from the media with ffmpeg
* Infer the correct processed audio file extension based on actual
codec to avoid ffmpeg errors
We need to support more extensions and make audio extraction dynamic,
as we shipped transcript in production and it led to user complaints
requesting more formats.
Speaker-to-participant assignment relie on WhisperX word timings, but
incorrect word durations in the output can lead to inaccurate overlap
scoring and wrong user attribution. Add a custom heuristic to trim
overly long word durations before computing assignments.
When duration is not reported in the files metadata,
we directly infer the duration from the audio packets.
This prevents errors on webm files.
Very simple audio & video test files have been added
that cover relevant usecases to prevent regressions.
Introduce a new user assignment mechanism to for more friendly output
than the current (SPEAKER_0, SPEAKER_1, ...). Use the VAD metadata to
compare speech intervals with those returned by WhisperX. User with the
highest overlap score above a defined threshold is assigned to each segment.
This method allows for multi-speaker scenarios for a single account.
Florent Chehab